Adaptive and wearable forearm EMG for interacting with different users and tasks

Electromyography, otherwise known as EMG, is the study of the electrical properties of our muscles. Significant amounts of funding and research have developed it into one of the leading technologies used in prosthesis, but it also shows tremendous potential as an EMG based human machine interface. H...

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Main Author: Cannan, James Astley Robert
Published: University of Essex 2014
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Online Access:http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.616993
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spelling ndltd-bl.uk-oai-ethos.bl.uk-6169932016-08-04T03:36:00ZAdaptive and wearable forearm EMG for interacting with different users and tasksCannan, James Astley Robert2014Electromyography, otherwise known as EMG, is the study of the electrical properties of our muscles. Significant amounts of funding and research have developed it into one of the leading technologies used in prosthesis, but it also shows tremendous potential as an EMG based human machine interface. However, it encompasses restrictions that prevent the general public from adopting the technology. This thesis focuses on improving EMG based Human Machine Interaction (HMI), in order to take a step towards making EMG systems easier to use for the general public. The nature of this research investigates novel approaches at reducing problems with multi-user interaction. Firstly, by investigating optimum electrode configurations with simple signal processing and machine learning to test an EMG gesture recognition system. Secondly, by using forearm circumference as an estimator of Maximum Voluntary Contraction (MCV), for use in an automatic threshold calibration technique, which includes the development of automatic circumference measuring armbands to make measurements and calibration completely autonomous. The third stage of this thesis investigates how EMG, circumference, and a combination of both, can be used for biometrically identifying a user. This benefits systems that require storing and retrieving past data or settings, and has promise for automatic retrieval of past training data. This is particularly useful for enhancing multi-user interactions, as each user will then be able to use their own previous data on an EMG system, which has been shown to be better than using other user's data. The final stage of this thesis creates an EMG and motion sensor fusion armband, to investigate how sensor fusion can enhance EMG interaction, with potential applications in robot tele-operation, Human Computer Interfaces (HCI) for amputees, and 3d object manipulation.616.7407547University of Essexhttp://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.616993Electronic Thesis or Dissertation
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topic 616.7407547
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Cannan, James Astley Robert
Adaptive and wearable forearm EMG for interacting with different users and tasks
description Electromyography, otherwise known as EMG, is the study of the electrical properties of our muscles. Significant amounts of funding and research have developed it into one of the leading technologies used in prosthesis, but it also shows tremendous potential as an EMG based human machine interface. However, it encompasses restrictions that prevent the general public from adopting the technology. This thesis focuses on improving EMG based Human Machine Interaction (HMI), in order to take a step towards making EMG systems easier to use for the general public. The nature of this research investigates novel approaches at reducing problems with multi-user interaction. Firstly, by investigating optimum electrode configurations with simple signal processing and machine learning to test an EMG gesture recognition system. Secondly, by using forearm circumference as an estimator of Maximum Voluntary Contraction (MCV), for use in an automatic threshold calibration technique, which includes the development of automatic circumference measuring armbands to make measurements and calibration completely autonomous. The third stage of this thesis investigates how EMG, circumference, and a combination of both, can be used for biometrically identifying a user. This benefits systems that require storing and retrieving past data or settings, and has promise for automatic retrieval of past training data. This is particularly useful for enhancing multi-user interactions, as each user will then be able to use their own previous data on an EMG system, which has been shown to be better than using other user's data. The final stage of this thesis creates an EMG and motion sensor fusion armband, to investigate how sensor fusion can enhance EMG interaction, with potential applications in robot tele-operation, Human Computer Interfaces (HCI) for amputees, and 3d object manipulation.
author Cannan, James Astley Robert
author_facet Cannan, James Astley Robert
author_sort Cannan, James Astley Robert
title Adaptive and wearable forearm EMG for interacting with different users and tasks
title_short Adaptive and wearable forearm EMG for interacting with different users and tasks
title_full Adaptive and wearable forearm EMG for interacting with different users and tasks
title_fullStr Adaptive and wearable forearm EMG for interacting with different users and tasks
title_full_unstemmed Adaptive and wearable forearm EMG for interacting with different users and tasks
title_sort adaptive and wearable forearm emg for interacting with different users and tasks
publisher University of Essex
publishDate 2014
url http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.616993
work_keys_str_mv AT cannanjamesastleyrobert adaptiveandwearableforearmemgforinteractingwithdifferentusersandtasks
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